Synergistic Effects between Phosphorylation of Phospholamban and Troponin I Promote Relaxation at Higher Heart Rate

We hypothesized that the extent of frequency-dependent acceleration of relaxation (FDAR) would be less than that of isoproterenol-(ISO-)dependent acceleration of relaxation (IDAR) at the same increment of heart rates, and ISO may improve FDAR. Cardiac function and phosphorylation of PLB and cTnI were compared in pacing, ISO treatment, and combined pacing and ISO treatment in isolated working heart. The increase in cardiac output and the degree of relaxation was less in pacing than in ISO treatment at the same increment of heart rates. The increasing stimulation frequency induced more significant relaxant effect in ISO perfusion than that in physiological salt perfusion. The pacing only phosphorylated PLB at Thr17, but ISO induced phosphorylation of cTnI and PLB at Ser16 and Thr17. Those results suggest that the synergistic effects of PLB and cTnI induce higher degree of relaxation which makes a sufficient diastolic filling of the ventricle at higher heart rate

Comparative study on the synergistic effect of POSS and graphene with melamine phosphate on the flame retardance of poly(butylene succinate)

Flame retardant poly(butylene succinate) (PBS) composites were prepared by melt blending PBS with melamine phosphate (MP), using graphene or polyhedral oligomeric silsesquioxanes (POSS) as synergists. The comparative study on the effect of POSS and graphene on the mechanical, thermal properties and flammability of flame retardant PBS was investigated. The addition of POSS or graphene further improved the LOI values of the flame retardant PBS, and V0 rating was obtained for the formulation containing 18 wt % MP and 2 wt% graphene. The incorporation of POSS and graphene reduced the crystallization of PBS, but improved the tensile strength. The presence of graphene exhibited superior thermal-oxidative resistance of the char layer compared to POSS, which effectively retarded the mass and heat transfer between the flame and the burning substrate, thus the heat release rate and total heat release of the flame retardant PBS composites containing graphene was significantly reduced during combustion

Undeca­carbonyl-μ2-methane­thiol­ato-μ2-[(pyridin-2-yl)methane­thiol­ato]-μ4-sulfido-tetra­iron(II)(2 Fe—Fe)

The title compound, [Fe4(C6H6NS)(CH3S)S(CO)11], com­prises two butterfly-shaped sub-cluster cores, Fe2S2N and Fe2S2, joined together by a spiro-type μ4-S atom. The (pyridin-2-yl)methane­thiol­ate ligand is attached to the Fe2(CO)5 unit in a μ-κN:κ2 S mode, and the methane­thiol­ate ligand is coordinated to the Fe2(CO)6 unit in a μ-κ2 S fashion

Exploiting Label Uncertainty for Enhanced 3D Object Detection from Point Clouds

Accurate detection of objects from LiDAR pointclouds is crucial for autonomous driving and environmentmodeling. However, uncertainties in ground truth labels due toocclusions, sparsity, and truncation can hinder model trainingand performance. This paper introduces two strategies to addressthese issues: 1) Soft Regression Loss (SoRL) and 2) DiscreteQuantization Sampling (DQS). SoRL utilizes Gaussian distributionsfor object predictions, measuring uncertainty based on theprobability of ground truth labels within these distributions. Thismethod effectively accounts for deviations in object location andorientation. Meanwhile, DQS introduces uncertainty scores fordynamic sample selection, aiming to refine the quality of positivesamples for regression. Based on the proposed modules, we designa lightweight multi-stage object detection framework. Notably,these modules can enhance existing 3D object detection methodswithout affecting significantly inference speeds. Experimentsover benchmark datasets show the effectiveness of our method,especially for cars in sparse point clouds

Using Dempster-Shafer’s evidence theory for query expansion based on freebase knowledge

Query expansion is generally a useful technique in improving search performance. However, some expanded query terms obtained by traditional statistical methods (e.g., pseudo-relevance feedback) may not be relevant to the user's information need, while some relevant terms may not be contained in the feedback documents at all. Recent studies utilize external resources to detect terms that are related to the query, and then adopt these terms in query expansion. In this paper, we present a study in the use of Freebase, which is an open source general-purpose ontology, as a source for deriving expansion terms. FreeBase provides a graph-based model of human knowledge, from which a rich and multi-step structure of instances related to the query concept can be extracted, as a complement to the traditional statistical approaches to query expansion. We propose a novel method, based on the well-principled Dempster-Shafer's (D-S) evidence theory, to measure the certainty of expansion terms from the Freebase structure. The expanded query model is then combined with a state of the art statistical query expansion model - the Relevance Model (RM3). Experiments show that the proposed method achieves significant improvements over RM3